A biometric monitoring system

Abstract

A system (1) for biometric monitoring of a subject (2), is provided comprising; a sensor device (100), having a sonic sensor (300), for biometric monitoring of the gastro-intestinal system (4); sensing data (5) comprising sound data acquired at the at least one sensor device (100);an analysis module (40) for establishing, based on periodicity and / or intensity of the biometric sound data, a first subset (11) of the first set of sensing data (10) and a second subset (12) of the sensing data (5); wherein the second subset (12) is discrete from the first subset (11), and wherein the first subset (11) is associated with a first biometric state of the gastro-intestinal system and the second subset is associated with a second biometric state; an output device (50) for providing a biometric indicator based on at least one of the first biometric state or the second biometric state.

Description

[0001] A BIOMETRIC MONITORING SYSTEM

[0002] Field

[0003] The present invention relates to a system and a method for non-invasive biometric monitoring of a subject. In particular, the present invention relates to a system and method for biometric monitoring of a subject, including a system and method for exvivo biometric monitoring of the heart, lung or gastro-intestinal system of a subject.

[0004] Background

[0005] Modern medicine, including human and veterinary medicine, requires accurate and reliable means to detect and interpret the function of various biological systems including heart, lung and gastro-intestinal systems. More recently, advances in computational power have enabled a new means, known as digital twins, to analyse, interpret and simulate systems such as biological systems. Digital twins can be used to understand the state of the system, determine if it is operating as expected and simulate how its current operation may affect its future operation.

[0006] A digital twin aims to simulate in a computer a physical system. To do this, it must have at least: i) a physical system that it is simulating, for example a biological system such as a human, or a sub-system, such as a human’s gastro-intestinal system; ii) a means to analyse the physical system’s state, such as a scan of the system, or data from body-worn sensors that provide information as to how the physical system is operating; iii) a mathematical model of the system that can ingest the sensor data and use this to make predictions of any or all of the present, future, and past states of the system.

[0007] Modern imaging systems such as ultrasound imaging, CT scan or MRI scans can provide excellent insights as to the physical state of a system, but are not portable and require a high level of training to operate the tools and interpret their results. Conventional, widely-available sensor systems such as digital stethoscopes, digital thermometers and medical-grade blood- oxygen sensors collect a limited range of medical data, and can be used at home or in a clinical setting. However, such sensors are most often used as part of short examinations, or to monitor basic continuous parameters such as heart rate or blood oxygen. They do not provide extensive insight into biological systems as a result of their limited scope. Some biological systems, such as the gastro-intestinal system, have natural cycles that can last for several minutes up to several hours. To understand these systems, data is required over longer timeframes in order to build accurate descriptions of the system. An example is a Migrating Motor Complex (MMC) cycle, which is the name given to the natural cycle of the bowel as it goes through various phases of operation or biometric states. These are I) Quiescence; II) Random low-amplitude activity; III) Regular high-amplitude bursts; IV) Short transition, and may usually last in total between 60 minutes and 4 hours unless interrupted by an event such as a meal. Tracking such cyclical activity over long time periods brings additional challenges such as the need for sensors to operate without the need of a human operator, and for the sensor to be discreet such that it does not unduly affect the comfort of the patient or affect the ability for the clinical team to carry out their work, such as changing dressings. For regular home-based monitoring for multi-hour periods, it is also desirable that the monitoring system does not unduly impede daily activities.

[0008] All sensors are subject to some amount of noise, whether from internal noise or external noise. In a body sensor, noise may be due to external signals such as external sounds and internal noise such as electronic noise and system resonance. It is beneficial to design a sensor such that such noise does not present in the data by, for example, insulating the sensor from external sounds and tuning out resonance. An alternative or complementary approach is to provide multiple sensors that can detect the desired signal and the noise elements to differing degrees, allowing separation and cancellation of the noise elements during subsequent processing. In some environments, such as for a first responder in noisy industrial settings or high traffic areas, the level of noise may so high as to overpower the signal or overload the sensor. In such instances, it may be necessary to switch to an alternative method of sensing more suited to high-noise environments. Some digital stethoscopes use a piezo sensor to directly monitor the movement of the stethoscope diaphragm but this is prohibitively expensive and complex to include in many designs.

[0009] The usefulness of a medical sensor and a digital twin requires that the data it provides can be used to guide the care of the patient. In certain environments, and for certain conditions, this brings conflicting challenges. In hospitals, there are logistical, comfort, resource and financial challenges to monitoring patients, especially when the patient’s condition may come and go, such as shortness of breath or bowel conditions such as ileus, diarrhoea or constipation, or when the patient may have wounds, cannulas or other objects on them that limit their ability to move or to position sensors. Such limitations means that it becomes impossible to monitor the majority of patients even when monitoring would benefit the care of the patient. Further, in a home environment, there may be limited knowledge of the correct positioning for sensors and depending on patients for consistent application is unreliable.

[0010] Medical sensors must operate in a clean environment and must themselves be clean. This can be a particular challenge with long term monitoring solutions. One way of achieving this is to ensure that sensors are manufactured in a clean environment, sealed and used only once. An alternative way of achieving a high level of cleanliness is by designing the sensor such that it can be cleaned. GB2616852A included by reference discloses one such solution.

[0011] As a further challenge, different types of model and data analysis often require different data characteristics. Long term monitoring as discussed above requires a portably power solution or battery data transmission is power intensive. Some models require very high data rates for short time periods, such as analysing a specific event such as a movement, while other models require lower data rates over longer timeframes, such as monitoring bowel activity.

[0012] The present invention seeks to address these and other disadvantages encountered in the prior art by providing an improved monitoring system for biometric systems and method of monitoring biometric systems. A sensor device is in the form of a skin-worn sensor device and associated algorithms optionally including developing digital twins of the body, for determining health metrics also known herein as biometric indicators. The system may be associated with monitoring heart, lung and gastro-intestinal function.

[0013] Summary of Invention

[0014] According to a first aspect, there is provided, a system for biometric monitoring of a gastrointestinal system of a subject, the system comprising; at least one sensor device, having a sonic sensor, for biometric monitoring of the gastro-intestinal system, and collecting a first set of sensing data comprising sound data acquired at the at least one sensor device; a processor including, an analysis module for establishing, based on periodicity and / or intensity of the biometric sound data, a first subset of the first set of sensing data and a second subset of the first set of sensing data; wherein the second subset is discrete from the first subset, and wherein the first subset is associated with a first biometric state of the gastro-intestinal system and the second subset is associated with a second biometric state; an output device for providing a biometric indicator based on at least one of the first or second biometric states to a user. Optionally; the processor including a filter for removing, from the sensing data, data associated with non-biometric sounds.

[0015] Optionally, the filter comprises an artificial intelligence engine.

[0016] Optionally, the system includes a base station comprising a transceiver, the filter, the analysis module and the output device, the at least one sensor device is a remote sensor device, remote from the base station and each includes a transceiver for exchanging data including the sensing data with the base station.

[0017] Optionally, the transceiver comprises a radio, Wi-Fi or Bluetooth transceiver.

[0018] Optionally, the base station comprises a personal mobile device of a user.

[0019] Optionally, the filter includes a compression module comprising a bandpass filter, wherein the frequency of the sensing data is indicative of whether the sensing data is associated with biometric sounds originating in the gastro-intestinal system.

[0020] Optionally, the system further comprises a digital twin module of the monitored gastrointestinal system.

[0021] Optionally, the at least one sensor device comprises: a diaphragm comprising a first surface acoustically couplable with skin of the subject and a second surface acoustically coupled with the at least one sonic sensor; and an attachment means for holding the sensor device to the skin of the subject.

[0022] Optionally, further comprising a chamber containing a volume of gas, wherein the second surface of the diaphragm is in fluid communication with the volume of gas and the at least one sonic sensor is in contact with the volume of gas in the chamber.

[0023] Optionally, the attachment means comprises an adhesive layer for adhering the sensor to the skin of the subject, arranged adjacent to the first surface of the diaphragm and preferably adhered thereto.

[0024] Optionally, further comprising at least one movement sensor configured to detect movement of a subject. Optionally, the movement sensor comprises an accelerometer for detecting the magnitude and direction of acceleration forces and / or moments, and optionally wherein the accelerometer comprises a multi-axis accelerometer and / or inertial measurement unit (IMU)

[0025] Optionally, further comprising an external sensing component configured to monitor an external environment of the sensor device preferably the external sensing component is an external sonic sensor.

[0026] Optionally, the at least one sonic sensor comprises a plurality of sonic sensors, and preferably wherein each sonic sensor of the plurality of sonic sensors has a fixed position and orientation relative to each other sonic sensor for locating the origin of the biometric sounds.

[0027] Optionally, at least one sonic sensor of the plurality of sonic sensors is configured to have a substantially different sensitivity relative to at least one other sensor of the plurality of sonic sensors.

[0028] Optionally, at least one of the one or more sensor devices includes a locating device for measuring a location of a second sensor device of the one or more sensor devices relative thereto, and preferably wherein said location comprises a direction and a distance.

[0029] Optionally, including a temperature sensor for measuring the temperature of the volume of gas in the chamber.

[0030] Optionally, the attachment means including an adhesive layer located in use between the sensor device and the subject 2 and extending therefrom and a patch including a pocket for accepting the sensor device adhered to the subject by the adhesive layer.

[0031] Optionally, the at least one sonic sensor comprises a sonic receiver and a sonic emitter for measuring movement of an organ or tissue of the subject, and optionally wherein the sonic emitter operates at a frequency of between 20kHz and 500kHz.

[0032] A second aspect of the current invention provides a method for determining a biometric indicator from the gastro-intestinal system of a subject, the method comprising: receiving, at a processor, sensing data comprising biometric sound data acquired from at least one sensor device for biometric monitoring of the gastro-intestinal system; establishing, based on periodicity and / or intensity of the biometric sound data, a first subset of the sensing data and a second subset of the sensing data; wherein the second subset is discrete from the first subset, and wherein the first subset is associated with a first biometric state of the gastro-intestinal system and the second subset is associated with a second biometric state of the gastro-intestinal system; determining the biometric indicator based on at least one of the first or second biometric state; and outputting the biometric indicator. Optionally, filtering, at a filter, the first set of sensing data to remove data associated with non-biometric sounds;

[0033] Optionally, collecting sensing data at a sensing device wherein the sensing data comprises biometric sound data.

[0034] Optionally, the first subset corresponds to a first discrete time period, and the second subset corresponds to a second discrete time period.

[0035] Optionally, the first biometric state comprises one phase of operation of a migrating motor complex (MMC) cycle and the second biometric state comprises another different phase of operation of the migrating motor complex (MMC) cycle.

[0036] Optionally, the method further comprises: establishing, based on periodicity and / or intensity of the biometric sound data, a third subset of the first set of sensing data associated with a third biometric state of the gastro-intestinal system, and a fourth subset of the first set of sensing data associated with a fourth biometric state of the gastro-intestinal system; wherein the third and fourth biometric states comprises further different phases of operation of a migrating motor complex (MMC) cycle.

[0037] Optionally, the third subset corresponds to a third discrete time period, and the fourth subset corresponds to a fourth discrete time period.

[0038] Optionally, the first biometric state comprises phase I of operation of a migrating motor complex (MMC) cycle, the second biometric state comprises phase II of operation of the migrating motor complex (MMC) cycle, the third biometric state comprises phase III of operation of the migrating motor complex (MMC) cycle, and the fourth biometric state comprises phase IV of operation of the migrating motor complex (MMC) cycle. Optionally, phase I is a quiescence phase; phase II is a random low-amplitude activity phase; phase III is a regular high-amplitude burst phase; and / or and the phase IV of operation is a short transition phase.

[0039] Optionally, the biometric indicator comprises a time, a time period, and / or an intensity of the biometric state for at least one of: the first biometric state, second biometric state, third biometric state and / or fourth biometric state.

[0040] Optionally, the biometric indicator comprises a mean intestinal rate across one or more of: the first biometric state, second biometric state, third biometric state and / or fourth biometric state.

[0041] Optionally, the biometric indicator comprises a relative sequence of at least two of: the first biometric state, second biometric state, third biometric state and / or fourth biometric state and / or the biometric indicator comprises identification of the MMC cycle, absence of the cycle and or cycle time.

[0042] Optionally, including receiving at the processor movement data of a subject collected at a movement sensor of a sensing device, wherein said movement data is included in the sensing data and associated with the biometric sound data.

[0043] Optionally, comparing at least one of the first subset, second subset, third subset, the fourth subset of the first set of sensing data and / or the second set of sensing data to a digital twin model of the gastro-intestinal system;

[0044] Optionally, the method further comprises: based on the comparison to the digital twin model, determining that a difference between at least one subset of the first set of sensing data and the digital twin model exceeds a threshold value; and in response to the determination, issuing the biometric indicator (14) and / or amending the digital twin model (502).

[0045] Optionally, the biometric indicator is determined based on a prediction of the amended digital twin model and / or the biometric indicator is a prediction of the digital twin. Optionally, the sonic sensor of the at least one sensor device is an ultrasonic transceiver including a sonic emitter and a sonic receiver; the method including emitting by the sonic emitter, an emitted burst of sound waves and subsequently receiving at the sonic receiver said emitted burst as a detected burst, determining movement and / or position of the diaphragm from the emitted and detected bursts.

[0046] Optionally, at a processor calculating the relative change of frequency and / or the relative time of the detected burst relative to the emitted burst; and determining movement and / or position of the diaphragm from the emitted and detected bursts therefrom.

[0047] Optionally, collecting the sensing data comprises collecting at a first sonic sensor a first set of sensing data and collecting at a second sonic sensor a second set of sensing data; and comparing the first set of sensing data and the second set of sensing data; based on the comparison, determining a delay in a signal indicative of a biometric sound between the first set of sensing data and the second set of sensing data; based on the delay, determining a distance D and / or direction of travel d of the biometric sound source.

[0048] Optionally, the first set of sensing data is acquired at a first sensor device, and wherein the second set of sensing data comprising biometric sound data acquired at a second sensor device.

[0049] Optionally, the at least one sensor device includes the first sonic sensor and the second sonic sensor.

[0050] Optionally, filtering the first set of sensing data to remove data associated with non-biometric sounds comprises applying an artificial intelligence model.

[0051] Optionally, the artificial intelligence model comprises at least one of: a statistical model, a machine learning model, a deep learning model, and / or a convolution neural network.

[0052] Optionally, the artificial intelligence model has been trained using data sets comprising each phase of a four-phase migrating motor complex (MMC) cycle.

[0053] Optionally, the system includes a computer readable medium comprising instructions which, when executed by the processor, cause the processor to perform one or more of the method steps above. Optionally, there is provided at least one sensor, having an IMU sensor element and at least one microphone element sensitive in at least the sonic range, a diaphragm, an acoustic chamber, a radio transceiver module, and a battery and in which the sensor device is adhered to a body by means of an adhesive patch and wherein at least one microphone element is positioned to detect sound from the diaphragm and wherein the IMU sensor is positioned to detect acceleration of the body; and; a base station having at least a radio transceiver module, memory, a processor and a source of power, wherein the base station and at least one sensor are able to exchange data via radio signals; and wherein the sensor device or plurality of sensor devices can be configured by the base station to stream sensed data to the base station.

[0054] Figures

[0055] Brief Description of Drawings

[0056] Embodiments will now be described, by way of example only and with reference to the accompanying drawings having like-reference numerals, in which:

[0057] Figure 1 shows an example of a system, comprising two sensor devices, a base station and a digital twin model running on the base station according to an embodiment of the current invention in which the invention is configured to drive a digital twin of the gastro-intestinal system.

[0058] Figure 2 shows a section view through a biometric sensor device according to the current invention.

[0059] Figure 3 shows a section view through variation of the biometric sensor device of figure 2 according to the current invention in which ultrasound is used to sense the relative position of the diaphragm in order to measure vibrations thereof.

[0060] Figure 4 shows a plan view of an arrangement of sensor devices held in position by an attachment means according to the current invention. The attachment means including an adhesive patch Figure 5 shows an example of a system according to the current invention comprising three sensor devices, a base station, a digital twin running on the base station and a plot of an MMC cycle of the subject. The location of a biological acoustic event is depicted as a black circle.

[0061] Figure 6 shows an idealised representation of sensing data including acoustic activity of varying magnitude over time collected from the gut of a subject. The phases of the MMC into which the levels of activity fall are also shown.

[0062] Figure 7 shows another variation of the sensor device of figure 2 including a conical face of the acoustic chamber for directing sonic waves to the sonic sensor.

[0063] Figure 8 shows a schematic of the system of the current invention.

[0064] Detailed Description

[0065] In response to the challenges outlined, aspects and / or embodiments seek to provide a means to monitor biometric data relevant to heart, lung and / or gastro-intestinal systems in the form of a body-worn sensor and data collection method. The invention aims to provide a practical means to monitor patients and provide information about biological cycles that last from seconds to several hours or even days. In particular, the invention is able to sense and monitor data that can be used to identify bowel activity and the Migratory Motor Complex cycle. In an alternative use, the sensor is able to monitor breathing cycles to determine unusual breathing and other cycle indicators of respiratory inflammation. In a second alternative use, the sensor is able to sense cardiac data, such as heart rate, heart murmurs and heart valve timing. In a complementary or alternative use, the sensor is able to sense accelerations and movement, such as walking, changing position, acceleration of the skin, for example due to heart, lung or gastrointestinal function.

[0066] The claimed monitoring system 1 may include of some or all of the following features:

[0067] 1. One or more body-worn sensing device(s) 100 including one or more sensors for sensing acceleration and / or vibration of the surface of the body over at least part of the infrasonic, sonic and optionally ultrasonic range together sonic signals detected by a sonic sensor 300.

[0068] 2. One or more sensors for sensing acceleration of the whole body. 3. A means 104 to attach each sensor device 100 to the body of the subject 2 so as to sense the state of at least one of the body’s 2 biological systems.

[0069] 4. A means to configure each sensing device to perform the sensing task required.

[0070] 5. A means to evaluate the sensed data and convert into a form suitable for onward transmission.

[0071] 6. A means to transfer sensed data to an intermediate processor.

[0072] 7. A means to reduce or remove noise from the sensed data such as a filter.

[0073] 8. A base unit or base station 60 that communicates with the sensor device 100 using a radio transceiver; each having a transmitter, receiver and / or transceiver 208 for communication therebetween.

[0074] When developing a sensing solution that can operate over a long period of time while being minimally invasive to the patient, the sensor device 100 has its own internal source of power. This power is most often provided by a battery. Further, it is often beneficial that the sensor can exchange data with a remote system wirelessly, such as to transmit sensed data to a model running on a remote system. This data exchange is often provided by a radio transceiver, such as a Bluetooth module. Often, the designer of such a system must consider the conflicting requirements of a small battery size with the power needs of the sensors and the radio transceiver.

[0075] According to the first aspect, the sensor device 100 includes a means to sense sonic vibrations of the skin including a sonic sensor 300. A means to sense sonic vibrations comprises:

[0076] A thin diaphragm 220 that on one surface, here referred to as the fore side or first side 221 , is in use designed to contact the skin of a subject 2. The diaphragm 220 is acoustically coupled with the skin, such that acoustic waves reaching the surface of the skin act to move the diaphragm 220 component. The diaphragm 220 may contact the skin directly or the first side 221 may include an intermediate material between the diaphragm and the skin, such as an adhesive layer or adhesive patch 107 which may form part of the same sensor unit 100 or may be included in the means for attachment 104 of the sensor unit 100 to the subject 2. The adhesive patch 107 may be applied prior to or at the time of use and removed, reconditioned and / or replaced after use. The sonic sensor 300 may be included in a sensor unit or sensor device 100 as shown in figure 2.

[0077] The aft side or second side 222 of the diaphragm 220 is exposed to a means to monitor sonic vibrations 300 emanating from the diaphragm surface 222, also referred to as a sonic sensor 300. A sonic sensor 300 may include a microphone or sonic receiver 301 placed so as to be sensitive to the sonic vibrations from the diaphragm 220 or acoustically connected there to. The diaphragm 220 and microphone 301 are preferably located within or facing a chamber 203, containing therein a volume of gas such as air for conducting the sonic vibrations from the diaphragm 220 to the microphone 301 .

[0078] An acceleration or movement sensor 600, such as a multi axis accelerometer or an Inertial Measurement Device (IMU) 207 and more specifically a MEMS IMU is mechanically coupled to the housing 201 so as to detect movement of the body of the subject and to detect the magnitude and direction of acceleration forces such as gravity, so as to enable estimation of its orientation, to establish movement of the subject and so as to enable the sensing of acoustic signals in the infrasonic range.

[0079] An electronics module or interconnected modules comprising the sensors 300, 301 , 302, 215, 216, 207 a processor, a battery, a means to charge the battery, and a radio transceiver is or are contained within an outer housing which also contains the chamber, so as to create the sensor device.

[0080] Data from the sensor elements within the sensor unit are recorded synchronously so as to enable acoustic data analysis to be performed with the context of motion, for example, to identify the interrelationship between movement and bowel activity; temperature, to accurately determine the speed of sound within the chamber 203 for improving accuracy of sonic measurement; and for temporal measurement of sonic data from different sensors such that the location of origin of a biometric sound can be determined. Synchronous recording and data analysis may be achieved by the first data set 10 and the second data set 20 including a time stamp for synchronising the data, providing the relative arrival time of sensed acoustic event at each sensor device.

[0081] In overview, and without limitation, the application discloses a monitoring system 1 for biometric monitoring of gastro-intestinal system 4 of a subject 2. The system 4 includes one or more sensor devices 100, including a sonic sensor 300 for biometric monitoring of the gastro-intestinal system 4 of a patient 2. The sonic sensor 300 collects a first data set 20 comprising sound data from which biometric sounds may be isolated and from these sounds gut activity may be determined. A filter 30 may contribute to this isolation and additionally reduce the size of the sensed data set 5 by removing non-biometric sounds. Based on the number of, regularity, periodicity of these biometric sounds an analysis module 40 determines at least a first subset and a second subset of the first data set to be isolated. Periodicity may be determined by establishing the frequency and time between peaks and / or troughs in collected biometric sounds. Wherein, the first subset is associated with a first biometric state of the gastro-intestinal system and the second subset is associated with a second biometric state of the gastro-intestinal system. Sound data may include sonic, ultrasonic or infrasonic data. A sonic sensor 300 may detect any of sonic, ultrasonic or infrasonic data. The skilled person will understand that the arrangement shown in figure 1 may also be used to monitor heart, lung or other bodily function if repositioned elsewhere on the subject’s 2 body.

[0082] The filter 30 may include a bandpass filter, an Al engine or other filter suitable for removing and / or identifying biometric or non-biometric sounds from the sensing data 5. The band pass filter may be used to remove frequencies not associated with sounds made by biometric systems such as gut sounds. The band pass filter may filter sounds above 1000Hz, sound outside of 100Hz to 700Hz or preferably sound outside of 200Hz to 600Hz. The skilled person will understand that biometric sounds are generated outside of these ranges and may be useful for analysis but the aforementioned ranges are most useful for analysis envisaged by the current invention.

[0083] If an Al engine or model is included to isolate non-biometric sounds from the sensing data 5; the Al model if included may be a machine learning model trained on training data including validated isolated bowel sounds or for identifying noise in samples. The Al model receives sensing data and outputs sonic data to be removed or kept or may flag a noisy trace if noise is identified.

[0084] A first embodiment describes a biological sensor device 100 according to the current invention for the monitoring of bowel activity.

[0085] With reference to Figure 1 , a monitoring system 1 is shown that comprises a plurality of sensor devices 100; specifically, a first sensor device 101 attached in the abdominal region of a patient 105 using an attachment means 104 such as an adhesive patch 107 and a second sensor device 102 attached in another location in the abdominal region of a patient 105 using a similar attachment means 104. In some implementations, the location of the two sensor devices may be positioned such that they monitor two distinct areas of the bowel and are separated by a distance L that may be greater than 50mm, for example, 80mm or a distance between 50mm and 400mm, for example 150mm. The first sensor device 101 and the second sensor device 102 may be fixed by way of a single attachment means 104 that determines a known relative location between the two sensors including a distance D and a direction d. A model may rely on a mixture of data, such as data from a number of scans used to build a generic model, which can then be fed specific data from sensors that may then form a digital twin model of a measured system. It has been found the use of multiple sensors, positioned at various locations on a body providing multiple data streams is beneficial when building an understanding of the biometric system. Such a system facilitates improved understanding of the variation of readings across the body and the ability to locate the sources of a reading in particular the location of the source of a sonic event. For a model to understand and derive maximum benefit from the data, some context of the location of the sensors is needed, such as identification of their relative position. Such positioning can be achieved by manually measuring and feeding into the model the location of each sensor relative to the body and to the other sensors, but such a solution is time consuming and subject to errors. An alternative solution is to always use the same locations. However, the geometry of a body is not consistent from patient to patient and the ideal placement may not always be possible. Ideal placement may be impeded by a wound dressing, the stature of the subject may obstruct a preferred location or separation.

[0086] Optionally, sensors 101 and 102 each have a unique device ID 121 which may be a Bluetooth ID, a radio ID and / or a WI-FI ID and a passcode 122 on them. In an alternative embodiment not shown, the device ID or Bluetooth ID and passcode are contained within a 2d barcode.

[0087] In operation, the first sensor device 101 provides a first data set 10 and the second sensor device 202 provides a second data set 20. The first data set 10 and the second data set 20 include a time stamp for synchronous analysis. The monitoring system 1 includes a processor operable to determine the time difference between similar sonic data from the first data set 10 and the second data set 20 a distance and direction of the source of sonic data detected.

[0088] The two sensor devices 100 each comprise a radio transmitter or transceiver 208 for radio communication with a base unit or base station 60. The base unit 60 may be a remote computer 63, a central monitoring system 66 or as shown a mobile phone 64 running suitable communication software or app. A connection with each of the sensor units or sensor devices 100 is established by choosing the device IDs of the sensor units 100 from the base station 60 and inputting the associated passcodes.

[0089] The processor of the base unit 60 runs a digital twin simulation 502 of the gastro-intestinal tract 104 at a digital twin module 500 and determines a upper bound and lower bound of normal bowel activity. The monitoring system 1 uses the incoming sensed data 5 to create a first data set 10 and identify therefrom current activity of the digestive tract 4 of the subject 2 such as bowel activity. The processor 800 may include a digital twin model 500. By monitoring said current bowel activity data and comparing the first data set 10 against predicted upper bound and lower bound models of expected activity that may be provided by a the digital twin simulation 507 of the biological system being monitored, the digital twin module 500 is able to assess and / or determine whether the gut activity is normal or abnormal. Abnormal activity may be determined and reported if for example there are many interrupted MMC cycles occurring or if the overall level of bowel activity is low. An abnormal state triggers the digital twin 500 to run simulations to assess and / or determine the likely response to appropriate medical or lifestyle interventions, such as the use of medication to prevent diarrhoea or the likely effect of a period of fasting. The digital twin 500 then identifies the possible actions to improve the function of the bowel and reports these. The biometric indicator may include these reports or predictions of the digital twin model. Sensor data and simulation information is uploaded via a network to a database 56 for further processing and analysis.

[0090] Stages of the MMC may not be well defined in terms of regularity or intensity of noise, but may be determined within an envelope of activity, for example over an analysis period of 90-240min of data. The bowel is very rarely silent in a healthy person, but over the course of several hours, relative activity increases and decreases. Peaks and troughs in sensing data 5 may be established and periodicity can be determined from the peaks and troughs in this activity by the analysis module 40. In the plot shown in figure 6, more active times and less active times can be seen; these can be identified by the analysis module 40. Pattern-matching analysis of the data can be used to establish activity levels, a moving average filter may be applied in order to normalise sonic events over the analysis period. Alternatively, the analysis module 40 may count the number of sonic events that breach an intensity threshold. The phase of the MMC may be established based on the sensed data 5, in particular the periodicity and or intensity of the sonic data received and cycle activity profiles determined. In particular, a first subset 11 and a second subset 12 of the sensing data 5 can be established and each associated with a different phase of the MMC and a biometric indicator 14 issued based on one or more of the first subset 11 and second subset 12. Analysis may include peak to peak (high activity to low activity) and assess the time between these peaks.

[0091] In one aspect, the base station 103 uses Bluetooth location services, wifi location services, or GPS to identify the location of the devices 101 and 102 relative to the base station, and hence the relative location of the patient. With reference to Figure 2, the sensor device 100 is described. The sensor device 100 has a rigid outer body 201 manufactured from a plastic or polymer, for example a modified polycarbonate, acrylic, polystyrene or other suitable polymer. The sensor device 100 includes a diaphragm 220 that forms part of the external surface 200 of the sensor device 100. The diaphragm 220 includes a fore face or first side 221 that forms part of the external surface 200 of the sensor device 100. The diaphragm may be constructed of thin glass reinforced epoxy, having thickness less than 1 mm, preferably 0.2mm or less and most preferably 0.15mm. The diaphragm 220 is held or attached to the body 201 by a bonding ring 210. to the bonding ring 210 preferably includes a diaphragm damper 212 for damping movement at the outer edge of the diaphragm 220 so as to absorb vibrations originating from the device body 201. The diaphragm 220 is acoustically connected to one or more sonic sensors 300. The sensor device further includes a rigid board 209 extending across the inside of the body 201. An acoustic cavity 203 or acoustic chamber 203, formed between the diaphragm 220, the outer body 201 and the rigid board 209. The rigid board 209 is preferably a PCB 209a and holds components including a bottom port MEMS microphone 204, a second bottom port MEMS microphone 205, a rechargeable battery 206, one or more accelerometers 207, preferably an inertial measuring unit (IMU) 207, and a radio transceiver module 208. The one or more sonic sensors 300 are shown in figure 2 as microphones 204 and 205. Microphones 204, 205 are acoustically coupled to the acoustic chamber through small diameter holes through the PCB and preferably sealed thereto. The skilled person will understand that one or more sonic sensors 300 may be included within the scope of this disclosure.

[0092] In a variation on the device shown in figure 2, the sensor device may include an external sensor 320 as shown in figure 7 for monitoring an external environment of the sensor device 100. Preferably the external sensor 320 is a top port MEMS microphone for monitoring sounds from above the board and / or external to the sensor device 100 for providing external data for assisting a filter 30 in filtering non-biometric sounds from the data set 10. In a complementary or alternative embodiment not shown, the sonic sensor 300 comprises a top port MEMS microphone is mounted to the underside of the PCB to monitor the acoustic chamber 203 as an alternative to the use of top-mounted, bottom ported microphones 204, 205. The movement sensor 207 or IMU sensor 207 is mounted close to the edge of the PCB 209 so as to reduce noise caused by resonance of the PCB 209. For example, the IMU 207 is located less than 1 / 3 of the distance from the edge of the board to the centre of the board, for example at 1 / 5 of the distance. Alternatively the movement sensor 207 may be mounted to the body 201 to provide further rigidity. The PCB 209 is inserted into the case using a keyway 214, only partially shown in the cross-sectional figure 2. A wireless recharging module 211 is attached via an adhesive to the top of the inside face of the sensor and is electrically connected to the electronics PCB 209 for charging of the battery 206. The wireless charging module 211 removes the requirement for a charging connection which advantageously improves hygiene.

[0093] Figure 2 shows a preferred arrangement of the attachment means 104. The attachment means 104 may comprise an adhesive layer 107 comprising an intermediate layer between the diaphragm 220 and the skin of the patient 2 including adhesive on both sides. A first side 107a may be suitable for adhering to the skin of a subject, and the second side 107b suitable for adhering to the first side 221 of the diaphragm 220 for acoustically connecting the diaphragm 220 to the skin of the patient. The adhesive layer 107 includes an outer portion 109 that extends substantially beyond the body 201. The attachment means 104 shown further includes a patch 110 that includes a pocket 112 shaped for receiving the sensor device 100 and a flange 119 complementary to the outer portion 109 of the adhesive layer 107. The patch 110 is for supporting the sensor device such that the acoustic connection formed by the adhesive layer 107 between the skin of the patient and the diaphragm 220 is optimised. The extended outer portion 109 and complementary flange 119 allows the attachment means 104 to be substantially trimmed around the body, other sensors, cannulas or monitoring devices of the patient whilst maintaining adequate support of the sensor device 100 and acoustic connection of the diaphragm 220.

[0094] An alternative embodiment of the sensor device 100 is shown in Figure 3 that senses the position of the diaphragm 220 using ultrasound as well as or instead of using one or more microphones 301. Many of the same features of the sensor device 100 of figure 2 are included and are indicated by the same reference numerals. The sensor device 100 has a rigid outer body 201 , a diaphragm 220 comprised of glass reinforced epoxy, having thickness less than 1 mm and preferably less than 0.2mm, and most preferably 0.15mm. The diaphragm 220 is adhered to the outer body 201 by a bonding ring 210 that preferably includes a diaphragm damper 212. An acoustic cavity 203 is formed between the diaphragm 220, the outer body 201 and a rigid board 209. The acoustic cavity 203 preferably has a height H of between 2 and 20mm, preferably between 4 and 10mm, and most preferably 7mm. Acoustic damping material 310 may be attached to one or more and preferably all walls 212 of the acoustic cavity 203 to reduce reflection of ultrasound vibrations. The rigid board 209 is a PCB and holds components including the one or more sonic sensors 300. In this embodiment the sonic sensor 300 comprises a ultrasonic transducer 304 or sonic emitter 302 as well as a sonic receiver 301. Preferably the sonic transducer 304 comprises a MEMS microphone 304 capable of being configured as an ultrasonic transceiver for receiving ultrasonic waves, that includes the sonic receiver 301 and the sonic emitter 302. The sonic receiver 301 and the sonic emitter 302 to operable at a frequency of between 20kHz and 500kHz, preferably between 50kHz and 10kHz and most preferably at 80kHz and hereto referred to as an ultrasonic transducer 302 when emitting sound and ultrasonic microphone 301 when receiving sound.

[0095] Preferably, the sensor device 100 includes a first sonic sensor 304 and a second sonic sensor 305 therein. The first sensor device 100 is the MEMS microphone 304 and the second sonic sensor 305 is a second bottom port MEMS microphone 305 is similarly configured, a rechargeable battery 206, an inertial measuring unit (IMU) 207, and a radio transceiver module 208 are also held by the PCB 209. The microphones 304 and 305 are acoustically coupled to the acoustic chamber through small diameter holes through the PCB. The IMU sensor is mounted close to the edge of the PCB 209 so as to reduce noise caused by resonance of the PCB 209. The PCB 209 is inserted into the case using a keyway, only partially shown in the cross-sectional figure. A wireless recharging module 211 is attached via an adhesive to the top of the inside face of the sensor and is electrically connected to the electronics PCB 209.

[0096] It is advantageous if the height H of the acoustic cavity 203 is greater than 1.5 wavelengths of the selected ultrasound frequency, as this dictates a minimum time to deploy three ultrasound oscillations. If the ultrasonic transducer is enabled for a time period equal to two cycles, then in a well-damped system, a period of one further oscillation is needed to return the oscillating diaphragm to a stationary position. It is advantageous to avoid operating the ultrasonic transducer at its resonant frequency or at a harmonic of its resonant frequency so as to increase control over the duration of oscillation and improve the dampening response. However, if greater ultrasound output is required, it may be a beneficial compromise to operate the ultrasonic transducer at or approaching its resonant frequency to maximise output. Under such conditions, a chamber height of greater than 4 times the wavelengths of the selected ultrasound frequency is beneficial.

[0097] In operation, the ultrasonic transducer 304 and / or 305 configured as a sonic emitter 302 is excited to oscillate for a period of one or more cycles, for example two cycles. For example, if a frequency of 80kHz is to be used, the excitation is applied for 25uS. The ultrasonic transceiver 304 is then returned to a state of a ultrasonic microphone or sonic receiver 301 or advantageously, the ultrasonic transducer 304 continuously monitors throughout the excitation thus not requiring the additional step of returning to a microphone 301 state. The ultrasound microphone 301 then senses the returning ultrasound wave. A mathematical analysis is conducted to calculate the time between the emitted and sensed waves, such as the time between sending and receiving the second peak of the second cycle. Through appreciation of the speed of sound in the cavity 203, the distance between the microphone 301 and the diaphragm 220 is calculated. The operation is repeated at least twice as frequently as is required to provide the required highest frequency of oscillation of the diaphragm that is to be sensed, for example, to monitor oscillation frequencies up to 8kHz, ultrasound is pulsed at least 16,000 times per second. The DC component of the distance measurements is removed to recover the AC oscillation of the diaphragm 220. In order to accurately determine the speed of sound in the cavity the sensor device 100 may include a temperature sensor 215 for measuring the temperature of the gas in the cavity 203.

[0098] Figure 7 shows the sensor device of figure 2 with the addition of a conical lower surface 209b to the board 209 for directing sound waves to the sonic receiver 301 .

[0099] Figure 4 shows a plan view of an embodiment in which a means for attachment 104 includes a patch 400 including means such as a pocket 112 for locating four sensor devices 401-404, each secured at known relative distances to each other. Each of said devices 401-404 are a sensor device 100 and preferably include a sonic sensor 300. Alternative arrangements not shown may include more or fewer sensor devices 100 in similar pre-determined offsets from each other. Such an embodiment may be used to apply a plurality of sensor devices 100 so as to monitor the bowel from multiple locations with known relative distances between each sensor device 100.

[0100] In operation, synchronous or near-synchronous data is sent to a base unit 60 preferably the synchronous data comprises a first data set 10 from the first sensor device 101 and a second data set 20 from the second sensor device 102. Alternatively, a sensor device 100 may include a plurality of sonic sensors 300 monitoring different sections of the diaphragm having known locations (not shown). The origin of an event or direction of origin is computed by assessing the arrival time of the event at each sonic sensor 300 and, based on a pre-calculated speed of sound in tissue, the origin of the sound may be found by a method such as triangulation.

[0101] Figure 5 shows a system including three sensor devices 100, 501-503, attached to the body of the subject 2, by an attachment means 104 of the current invention, at known locations with known distances between each sensor device 100. An acoustic event occurs at a location 505. The acoustic event may be sound issued by gut activity. Sensed synchronous data 10, 20 from each sensor device 100 wirelessly transmitted to a bedside base station 506. A Fourier transform of the data set 10, 20 sampled at each sensor device 100 is calculated. The variation in phase at one or more assessment frequencies is determined using the relative arrival time of the sensed acoustic event at each sensor device. The first assessment wavelength, is chosen to be between 10% and 150% of the approximate fundamental wavelength calculated from the nominal spacing of the sensor devices. The sensor devices may be positioned at distances of between 50mm and 400mm from each other, , preferably wherein each sensor is a different distance from one than the other. For example, sensor devices 501 and 502 may be 150mm apart, sensor devices 502 and 503 may be 120mm apart and sensor devices 503 and 501 may be 200mm apart. A nominal distance of 160mm may be chosen to aid the determination of an initial assessment wavelength. The frequency of such a wavelength can be calculated in the usual manner known to the skilled person, wave equation is v= f A, velocity = frequency x wavelength: frequency is therefore equal to wave speed I wavelength. For example, if the speed of soundwaves through tissue is approximated as 1540m / second, then a wavelength of 200mm would correspond to a frequency of 1540 / 0.2=7, 700Hz. In Figure 5, the acoustic event is depicted occurring at a location closest to sensor device 503 and furthest from sensor device 501. The relative difference in propagation distance is calculated by determining the difference in phase at a known frequency. The location of the acoustic event may then be to triangulated using the relative distances relative to each sensor device 100. Additional assessment wavelengths may be chosen to enhance or confirm the calculated distance, but one should be mindful that the phase component calculation must account for the possibility of a signal to a sensor being delayed by more than one wavelength. Such occurrences can be determined by selecting a relatively low frequency with long wavelength, such as 10% or 20%, for example, 25% of the nominal distance between sensors. However, at low frequencies the phase offset will be reduced and thus its calculation may be subject to increased noise. Thus, selection of higher frequencies can subsequently be used to refine the calculation.

[0102] In the embodiment shown in Figure 5, the base station 60 requests sensor data 10, 20 to be streamed to the base station 60 if the magnitude of the data, 10, 20 is above a noise threshold of 1 % of the total dynamic range. Alternatively, the sensor device 100 may include a data checker 36 that causes data to be transmitted when biometric sounds are recognised based on volume and / or frequency. The sensed data including positional data is used in the synchronisation of a digital twin 507 to the physical gastro-intestinal system being sensed. The sensed data is also processed, at an analysis module 40 of the processor 800, to extract information related to the amount of bowel activity, and this in turn is used to assess the MMC cycle phase which may be plotted on a graph 508, for example, if the bowel activity is calculated as reducing from a period of high activity, the algorithm will determine the bowel to be in Phase 4. Such a graph can be seen in figure 6.

[0103] Optionally, A sonic sensor 300 or other external sensing component 216 are mechanically attached to the body of the sensor device 100 in order to monitor noise, movements or vibrations of the external sensor 216 originating from external sources to the subject 2 and device 100, advantageously providing additional data signals that can be used to identify and remove noise from the signal.

[0104] Optionally, the sensor device 100 may have a plurality of sonic sensing microphones 300, 301 , 204, 205 arranged to detect different segments of the diaphragm 220 as shown in figure 3. A first data set 10 may be created including sonic data from a first sonic sensor 301 and a second data set 20 may be created including sonic data from a second sonic sensor 302. In such systems, the timing of signals into the different sensors 301 , 302 may be used as a means to determine the direction of travel of a signal across the diaphragm 220. This is enabled by the collection of synchronous data from the plurality of sonic sensors 300 The plurality of sonic sensors or microphones 300 may be configured to form an array such as a circular array. Advantageously, the plurality of data streams 10, 20 from these sensing microphones may be compared to identify the direction of a sound source, for example, to locate the relative direction of the source a bowel sound. Further, in such a system, the sensing microphones 300 may be configured to have different sensitivities, for example, a sensor may be configured to be less sensitive to low frequencies which advantageously may extend the dynamic response of the sensor device 100.

[0105] Optionally, the sensor 100 and base unit 60 incorporate position tracking capability using radio waves, for example by using Bluetooth location services or GPS. Advantageously, the position tracking capability can be used to track walking distance and route, monitor exercise activities and identify the current location of a patient, for example to monitor events such as the number and time of toilet visits or steps taken through a day. For example, such additional data can provide advantageous information when identifying how able a patient is to follow a recovery exercises routine, or whether a sensor device has moved out of an expected zone of operation, such as if unintendedly left on a patient at the time of patient discharge.

[0106] An accelerometer, or I MU provides acceleration data this can be used to detect position changes such as rolling in bed, sitting up, standing up. For example, moving from a lying position to a sitting or standing position may be detected through the change in direction of the acceleration due to gravity. Advantageously, such data can be used to add context to bowel activity data such as to understand if bowel activity is affected by the number and / or type of movements.

[0107] Location services can be used to identify the approximate distance or direction between sensor devices, such as the relative position of devices on a body. Advantageously, this enables an automatic estimation of the relative position of devices, which can then be used towards identifying the source direction of an acoustic event as sensed by two or more sensor devices.

[0108] The attachment means, or patch can be used to attach the sensor device to the body. Advantageously, the patch holds the sensor device at a constant location on the body. Optionally, the patch may hold more than one sensor device and provide a known relative orientation and distance between sensor devices. Advantageously, this provides a known separation of sensor devices which can be used towards accurately identifying the source direction of an acoustic event as sensed by two or more sensor devices.

[0109] The microphones 301 , 204, 205 of the sonic sensors 300 may include high-frequency or ultrasonic transceivers 304. In this arrangement, the microphone 300 is repurposed as an sound or ultrasound transducer 305. The transducer 305 may emit short burst of high- frequency sound or ultrasound as a sonic emitter 302 and then switched back to a microphone 301 to sense the reflected signal as a sonic receiver 301. By accurately measuring the time between the emitted and detected burst, the distance between the microphone and the reflecting surface, in this case the aft surface or the second surface 222 of the diaphragm 220, can be calculated. By rapidly, continuously repeating this process, movement and vibration of the diaphragm 220 can be recovered. Advantageously, this method may reduce the amount of unwanted noise in the system compared to a purely acoustic solution, or may be used to provide an alternative dynamic range to the sensing data 5 of the sensor device 100. Further, the velocity of the diaphragm 220 relative to the transceiver 304 may be calculated by accurately assessing the relative change of frequency of the reflective wave vs the emitted wave, for example, determining the doppler shift between the emitted and sensed frequencies. Such a system has the advantage of providing additional information on the movement of the diaphragm which may be used, for example, to confirm the movement of the diaphragm sensed using an alternative method. A purpose-specific ultrasonic transceiver 304 may be used to emit and / or receive the ultrasonic signal. Optionally, if a plurality of microphones 301 are used, then one or more of the microphones may be replaced by ultrasonic transducers 304 or emitters and one or more microphones may be ultrasonic microphones or receivers 305. In this configuration, one or more microphones may sense in the sonic frequency range. A configuration such as this has the advantage of not requiring the use of microphones suitable for transmitting ultrasound.

[0110] To enhance the sensor device 100 including the sonic sensor 300 configured in any of the aforementioned ultrasonic or near ultrasonic configurations, the chamber 203 walls 202 may be partially constructed from or coated in acoustic damping material 311 that has properties so as to dampen or absorb ultrasonic reflections. Advantageously reducing or eliminating secondary reflections, or to create local zones of reflection so as to advantageously allow the movement of the diaphragm 220 to be measured at a plurality of locations. For example so as to provide data that can be processed to determine the velocity of a signal arriving at different locations of the diaphragm at different times, advantageously allowing the relative direction of the source of the signal to be calculated.

[0111] A temperature sensor 215 may be included to monitor the temperature of the sensor device 100 and specifically the temperature of the gas in the acoustic cavity 203. The temperature measurement may be used as a means to refine the accuracy of computation of the speed of sound, which can advantageously improve the calculation of the position of the diaphragm 220.

[0112] The sensor device 100 and / or the sonic sensor 300 may be reconfigurable to switch between sonic and ultrasonic acoustic sensing configurations. The reconfiguration may occur automatically, for example, based upon an algorithm to monitor external noise levels, or may occur as a result of a trigger or new commands sent from the base station 60.

[0113] The base station may be a mobile phone 64. Advantageously, this enables the sensor device to send data to any mobile phone equipped with suitable radio transceiver and running suitable software to control and / or receive data from the sensor device. Alternatively or additionally, the base station 60 may be or include a purpose-specific device. Advantageously, the use of a purpose-specific device may lead to an improved repeatability and reliability of the invention. In a defined environment such as a ward the base station 60 may be a computer. The base station 60 may be operable to control and collect data from a plurality of sensor devices 100 attached to one or more subjects 2. Advantageously, such an arrangement enables a ward of patients to be monitored from a single base station 60.

[0114] The base station 60 or the sensor devices 100 may be operable to compare the relative geographic location of sensor devices 100 and their relative movement to detect whether they are attached to the same patient or subject 2.

[0115] Optionally, the base station 60 or the sensor devices 100 may be operable to use the relative geographic location of sensor devices 100 as determined from a location service and / or their relative movement and / or acceleration to detect if a sensor device 100 has been removed or if an additional sensor device 100 has been attached to a body 2.

[0116] Optionally, the data from the sensor device 100 is used to adapt a digital twin model 502 of the biological system being monitored, for example, to improve the correlation between the physical system of the subject 2 and the digital twin 500.

[0117] Optionally, the base station 60 may send data to a server 600 having greater processing power or a plurality of servers 600, allowing the data to be processed and used in the construction or simulation of the digital twin 500.

[0118] If a plurality of sensor devices are attached to a single body, data from each device including accurate time data may be used to determine the relative distance from one sensor to another by emitting an ultrasonic burst from one sensor and listening for the burst at one or more other sensors. Optionally, each sensor device may in turn emit an ultrasonic burst so as to build a map of relative distances between a number of devices.

[0119] A monitoring system may comprise a network of a plurality of sensor devices 100. The data from the networked devices 100 may be time-synchronised to facilitate accurate phase analysis of inbound signal in order to determine the directional origin of the signal.

[0120] Optionally, sensor devices may be configured according to their location to sense bowel, cardiovascular or respiratory information. Optionally, the sensor device 100 may internally monitor the sensed signals and transmit all sensed data to the base station, so as to provide as much data as possible to be subsequently analysed.

[0121] Optionally, the sensor device 100 may internally monitor the sensing data 5 and determine at a filter 30 if sensing data 5 is relevant or relates to biometric information and transmit only part of the sensed data 5 to the base station 60. The filter 30 may comprise an algorithm configured to determine if data is to be sent, such as to send data only if the data changes in magnitude by a predetermined amount and / or is recognised as a biometric sound or data. Such a system has the advantage of reducing the overall quantity of data required to be transmitted, thereby reducing the energy usage of the sensor device.

[0122] Optionally, the sensor device may compress the data before transmission using a lossless or lossy compression algorithm. Such a compression step has the advantage of reducing the overall quantity of data required to be transmitted.

[0123] Optionally, the sensor device may transmit data to the base station only when requested by an instruction sent from the base station or according to a schedule provided via the base station. In such instances, the sensor device may store data locally and transmit in bursts, or may partially or wholly shut down between periods of activity, for example, to conserve power.

[0124] Figure 8 illustrates a block diagram of one implementation of a monitoring system 1. The monitoring system 1 comprises a computing system 810 within which a set of instructions, for causing the computing system 810 to perform any one or more of the methods discussed herein, may be executed.

[0125] The computing system 810 shall be taken to include any number or collection of machines 820, e.g. computing device(s), that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methods discussed herein. That is, hardware and / or software may be provided in a single computing device, or distributed across a plurality of computing devices in the computing system. In some implementations, one or more elements of the computing system may be connected (e.g., networked) to other machines, for example in a Local Area Network (LAN), an intranet, an extranet, or the Internet. One or more elements of the computing system may operate in the capacity of a server or a client machine in a client-server network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. One or more elements of the computing system may be a personal computer (PC), a tablet computer, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a server, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine.

[0126] The computing system 810 includes controller circuitry 811 and a memory 813 (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM (RDRAM), etc.). The memory 813 may comprise a static memory (e.g., flash memory, static random access memory (SRAM), etc.), and / or a secondary memory (e.g., a data storage device), which communicate with each other via a bus (not shown).

[0127] Controller circuitry 811 represents one or more general-purpose processors such as a microprocessor, central processing unit, accelerated processing units, or the like. More particularly, the controller circuitry 811 may comprise a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, processor implementing other instruction sets, or processors implementing a combination of instruction sets. Controller circuitry 811 may also include one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like. One or more processors of the controller circuitry may have a multicore design. Controller circuitry 811 is configured to execute the processing logic for performing the operations and steps discussed herein.

[0128] The computing system 810 may further include a network interface circuitry 815. The computing system 810 may be communicatively coupled to an input device 820 and / or an output device 830, via input / output circuitry 817 including one or more radio transceivers 62. In some implementations, the input device 820 and / or the output device 830 may be elements of the computing system 810. The input device 820 may include an alphanumeric input device (e.g., a keyboard or touchscreen), a cursor control device (e.g., a mouse or touchscreen), an audio device such as a microphone, and / or a haptic input device. The output device 830 may include an audio device such as a speaker, a video display unit (e.g., a liquid crystal display (LCD), an organic light-emitting diode (OLED) display or a cathode ray tube (CRT)), and / or a haptic output device suitable for providing the Biometric indicator. In some implementations, the input device 820 and the output device 830 may be provided as a single device, or as separate devices. In some implementations, computing system 810 includes training circuitry 818. The training circuitry 818 is configured to train a method as described herein. The model may comprise a deep neural network (DNN), such as a convolutional neural network (CNN) and / or recurrent neural network (RNN). Training circuitry 818 may be configured to execute instructions to train a model that can be used to perform a method as described herein. Training circuitry 818 may be configured to access training data and / or testing data from memory 813 or from a remote data source, for example via network interface circuitry 815. In some examples, training data and / or testing data may be obtained from an external component, such as image acquisition device 840 and / or treatment device 850. In some implementations, training circuitry 818 may be used to update, verify and / or maintain the model.

[0129] In figure 7 the base station 60 is shown as including a mobile device 64 for receiving data from the one or more sensor devices 100 and a central monitoring system 66. The skilled person will understand that the mobile device 64 may be a user’s personal device or a specific base station 60 for receiving data from the one or more sensors 100. The base station 60 is also shown as including a central monitoring system 66 connected to the mobile device 64, the skilled person will understand that the base station 60 may include a mobile device 64 and or a central monitoring system 66 and each may receive data directly from the one or more sensor devices 100 within the scope of this claimed invention. The processor 800 may be present at both the mobile device 64 and central monitoring system 66 and cause functions to be carried out at the base station 60.

[0130] The various methods described herein may be implemented by a computer program. The computer program may include computer code (e.g. instructions) 1010 arranged to instruct a computer to perform the functions of one or more of the various methods described above. The steps of the methods described above may be performed in any suitable order. The computer program and / or the code 1010 for performing such methods may be provided to an apparatus, such as a computer, on one or more computer readable media or, more generally, a computer program product 1010, depicted in Figure 7. The computer readable media may be transitory or non-transitory. The one or more computer readable media 1020 could be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or a propagation medium for data transmission, for example for downloading the code over the Internet. Alternatively, the one or more computer readable media could take the form of one or more physical computer readable media such as semiconductor or solid state memory, magnetic tape, a removable computer diskette, a random access memory (RAM), a read-only memory (ROM), a rigid magnetic disc, and an optical disk, such as a CD-ROM, CD-R / W or DVD. The instructions 1010 may also reside, completely or at least partially, within the memory 813 and / or within the controller circuitry 811 during execution thereof by the computing system 810, the memory 813 and the controller circuitry 811 also constituting computer-readable storage media.

[0131] In addition, the modules and components can be implemented as firmware or functional circuitry within hardware devices. Further, the modules and components can be implemented in any combination of hardware devices and software components, or only in software (e.g., code stored or otherwise embodied in a machine-readable medium or in a transmission medium).

[0132] Unless specifically stated otherwise, as apparent from the following discussion, it is appreciated that throughout the description, discussions utilizing terms such as "receiving”, “determining”, “comparing ”, “enabling”, “maintaining,” “identifying,” “obtaining,” “detecting,” “generating,” “processing,” or the like, refer to the actions and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.

[0133] Any feature in one aspect or embodiment may be applied to other aspects or embodiments, in any appropriate combination. In particular, method aspects may be applied to system aspects, and vice versa. Furthermore, any, some and / or all features in one aspect can be applied to any, some and / or all features in any other aspect, in any appropriate combination. It will be understood that the above description of specific embodiments is by way of example only and is not intended to limit the scope of the present disclosure. Many modifications of the described embodiments, some of which are now described, are envisaged and intended to be within the scope of the present disclosure.

[0134] It should also be appreciated that particular combinations of the various features described and defined in any aspects can be implemented and / or supplied and / or used independently. It is to be understood that the above description is intended to be illustrative, and not restrictive. Many other implementations will be apparent to those of skill in the art upon reading and understanding the above description. Although the present disclosure has been described with reference to specific example implementations, it will be recognized that the disclosure is not limited to the implementations described, but can be practiced with modification and alteration within the spirit and scope of the appended claims. Accordingly, the specification and drawings are to be regarded in an illustrative sense rather than a restrictive sense. The scope of the disclosure should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

Claims

CLAIMS1 . A system (1) for biometric monitoring of a gastro-intestinal system (4) of a subject (2), the system (1) comprising; at least one sensor device (100), having a sonic sensor (300), for biometric monitoring of the gastro-intestinal system (4), and collecting sensing data (5); the sensing data including a first set of sensing data (10) comprising sound data acquired at the at least one sensor device (100); a processor (800) including a filter (30) for removing, from the sensing data (10), data associated with non-biometric sounds and an analysis module (40) for establishing, based on periodicity and / or intensity of the biometric sound data, a first subset (11) of the first set of sensing data (10) and a second subset (12) of the first set of sensing data (10); wherein the second subset (12) is discrete from the first subset (11), and wherein the first subset (11) is associated with a first biometric state of the gastro-intestinal system and the second subset is associated with a second biometric state; an output device (50) for providing a biometric indicator based on at least one of the first biometric state or the second biometric state.

2. A system according to claim 1 , wherein the filter (30) comprises an artificial intelligence engine (32).

3. A system (1) according to claim 1 or 2, wherein the system (1) includes a base station (60) comprising a transceiver (62), the filter (30), the analysis module (40) and the output device (50), the at least one sensor device (100) is a remote sensor device (106), remote from the base station (60) and each includes a transceiver (62) for exchanging data including the sensing data (5) with the base station (50).

4. A system (1) according to claim 3, wherein the transceiver (62) comprises a radio, Wi-Fi or Bluetooth transceiver.

5. A system (1) according to claim 3 or 4, wherein the base station (60) comprises a personal mobile device (64) of a user (2) or a central monitoring system (66).

6. A system (1) according to any preceding claim, wherein the filter (30) includes a compression module (34) comprising a bandpass filter (36), wherein the frequency of thefirst set of sensing data (10) is indicative of whether the sensing data (5) is associated with biometric sounds originating in the gastro-intestinal system (4).

7. A system (1) according to any preceding claim, further comprising a digital twin module (500) of the monitored gastro-intestinal system (4).

8. A system (1) according to any preceding claim, wherein the at least one sensor device (100) comprises: a diaphragm (220) comprising a first surface (221) acoustically couplable with skin of the subject (2) and a second surface (222) acoustically coupled with the at least one sonic sensor (300); and an attachment means (104) for holding the sensor device (100) to the skin of the subject (2).

9. A system (1) according to claim 8, further comprising a chamber (203) containing a volume of gas, wherein the second surface (222) of the diaphragm (220) is in fluid communication with the volume of gas and the at least one sonic sensor (300) is in contact with the volume of gas in the chamber (203) thereby acoustically connecting the second surface (222) and the at least one sonic sensor (300).

10. A system (1) according to claim 8 or 9, wherein the attachment means (104) comprises an adhesive layer (225) for adhering the sensor (100) to the skin of the subject (2), arranged adjacent to the first surface (221) of the diaphragm (220) and preferably adhered thereto.

11. A system (1) according to any preceding claim, further comprising at least one movement sensor (600) for detecting movement of the subject (2).

12. A system according to claim 11 , wherein the movement sensor (70) comprises an accelerometer (72) for detecting the magnitude and direction of acceleration forces and / or moments, and optionally wherein the accelerometer (72) comprises a multi-axis accelerometer (74) and / or inertial measurement unit (IMU).

13. A system (1) according to any preceding claim, further comprising an external sensing component (80) for monitoring an external environment of the sensor device (100) preferably the external sensing component is an external sonic sensor (216).

14. A system (1) according to any preceding claim, wherein the at least one sensor device (100) includes a first sensor device (101) and a second sensor device (102) and at least the first sensor deice (101) includes a locating device (105) for measuring a location of the second sensor device (102) relative thereto, and preferably wherein said location comprises a distance D and a direction d.

15. A system (1) according to any one of claims 1 to 14, wherein the at least one sonic sensor (300) comprises a plurality of sonic sensors (300), including at least a first sonic sensor (301) and a second sonic sensor (302), and preferably wherein the first sonic sensor (300) has a fixed, known position and orientation relative to the second sonic sensor (302) for locating the origin of the biometric sounds in the subject (2); preferably when dependent on claim 14 wherein the first sonic sensor (301) is located in the first sensor device (101) and the second sonic sensor (302) is located in the second sensor device (102).

16. A system (1) according to claim 15, wherein at least one sonic sensor (300) of the plurality of sonic sensors (300) is configured to have a substantially different sensitivity relative to at least one other sensor (300) of the plurality of sonic sensors (300).

17. A system (1) according to any preceding claim, wherein the at least one sonic sensor (300) comprises a sonic receiver (301) and a sonic emitter (302) for measuring movement of an organ or tissue of the subject, and optionally wherein the sonic emitter (302) operates at a frequency of between 20kHz and 500kHz.

18. A system (1) according to any one of claims 9 to 17, including a temperature sensor (216) for measuring the temperature of the volume of gas in the chamber (203).

19. A system (1) according to any preceding claim, wherein the attachment means includes an adhesive layer (107) located in use between the sensor device 100 and the subject 2 and extending therefrom and a patch (110) including a pocket 112 for accepting the sensor device (100) adhered to the subject by the adhesive layer (107).

20. A system (1) according to any one of claims 8 to 19, wherein the sonic sensor (300) of the at least one sensor device (100) is an ultrasonic transceiver (304) including a sonic emitter (302) and a sonic receiver (301);the system (1) operable to cause the sonic emitter (302) to emit a burst of sound waves, subsequently received at the sonic receiver (301), for establishing location and / or velocity of a second surface (222) of the diaphragm (220).21 . A method for determining a biometric indicator from the gastro-intestinal system (4) of a subject (2), the method comprising: receiving, at a processor (800), sensing data (5) comprising biometric sound data; acquired at a sonic sensor (300) of at least one sensor device (100) for biometric monitoring of the gastro-intestinal system (4); filtering, at a filter (30), the sensing data (5) to remove data associated with nonbiometric sounds; establishing, based on periodicity and / or intensity of the biometric sound data, a first subset (11) of the sensing data (5) and a second subset (12) of the sensing data (5); wherein the second subset (12) is discrete from the first subset (11), and wherein the first subset (11) is associated with a first biometric state of the gastro-intestinal system (4) and the second subset (12) is associated with a second biometric state of the gastrointestinal system (4); determining the biometric indicator (14) based on at least one of the first or second biometric state; and outputting the biometric indicator (14).

22. A method according to claim 21 , including collecting the sensing data (5) at a sensing device (100) wherein the sensing data (5) comprises biometric sound data.

23. A method according to any one of claims 21 to 22, wherein the first biometric state (11a) comprises one phase of operation of a migrating motor complex (MMC) cycle and the second biometric state (12b) comprises another different phase of operation of the migrating motor complex (MMC) cycle.

24. A method according to claim 23, wherein the method further comprises: establishing, based on periodicity and / or intensity of the biometric sound data, a third subset of the first set of sensing data associated with a third biometric state of the gastro-intestinal system, and a fourth subset of the first set of sensing data associated with a fourth biometric state of the gastro-intestinal system; wherein the third and fourth biometric states comprises further different phases of operation of a migrating motor complex (MMC) cycle.

25. A method according to claim 23 or 24, wherein the first biometric state comprises phase I of operation of a migrating motor complex (MMC) cycle, the second biometric state comprises phase II of operation of the migrating motor complex (MMC) cycle, the third biometric state comprises phase III of operation of the migrating motor complex (MMC) cycle, and the fourth biometric state comprises phase IV of operation of the migrating motor complex (MMC) cycle.

26. A method according to any of claims 21 to 25, wherein the biometric indicator (14) comprises a time, a time period, and / or an intensity of the biometric state for at least one of: the first biometric state, second biometric state, third biometric state and / or fourth biometric state.

27. A method according to any of claims 21 to 26, wherein the biometric indicator (14) comprises a mean intestinal rate across one or more of: the first biometric state, second biometric state, third biometric state and / or fourth biometric state.

28. A method according to any of claims 21 to 27, wherein the biometric indicator (14) comprises a relative sequence of at least two of: the first biometric state, second biometric state, third biometric state and / or fourth biometric state and / or the biometric indicator comprises identification of the MMC cycle, absence of the cycle and or cycle time.

29. A method according to any of claims 21 to 28 further including receiving at the processor (800) movement data (16) of a subject (2) collected at a movement sensor (600) of the sensing device, wherein said movement data (16) is included in the sensing data (5) and associated with the biometric sound data.

30. A method according to any of claims 21 to 29, further comprising comparing at least one of the first subset, second subset, third subset, the four subset of the sensing data (5) to a digital twin model (502) of the gastro-intestinal system (4); and based on the comparison to the digital twin model, determining that a difference between at least one subset of the first set of sensing data and the digital twin model (502) exceeds a threshold value; and in response to the determination, issuing the biometric indicator (14) and / or amending the digital twin model (502).

31. A method according to claim 30, wherein the biometric indicator (14) is determined based on a prediction of the amended digital twin model (503) and / or the biometric indicator (14) is a prediction of the digital twin (503).

32. A method according to any of claims 21 to 31 , wherein the sonic sensor (300) of the at least one sensor device (100) is an ultrasonic transceiver (304) including a sonic emitter (302) and a sonic receiver (301); the method including emitting by the sonic emitter (302) an emitted burst of sound waves and subsequently receiving at the sonic receiver (301) said emitted burst (321) as a detected burst (322), determining the time between the emitted burst (321) and the detected burst (322) to determine the distance to a second surface (222) of the diaphragm (220) and / or determining the doppler shift of the frequency between the emitted burst (321) and the detected burst (322) to determine the velocity of the second surface (222) of the diaphragm (220) the from the emitted and detected bursts (321 , 322).

33. A method according to claim 32 including at a processor (800) calculating the relative change of frequency and / or the relative time of the detected burst relative to the emitted burst; and determining movement and / or position of the diaphragm (220) from the emitted and detected bursts (321 , 322) therefrom.

34. A method according to any one of claims 22 to 33, wherein collecting the sensing data (5) comprises collecting at a first sonic sensor (301) a first set of sensing data (10) and collecting at a second sonic sensor (302) a second set of sensing data (20); and comparing the first set of sensing data (10) and the second set of sensing data (20); based on the comparison, determining a delay in a signal indicative of a biometric sound between the first set of sensing data and the second set of sensing data; based on the delay, determining a distance D and / or direction of travel d of the biometric sound source.

35. A method according to any of claims 21 to 34, wherein the first set of sensing data (10) is acquired at the first sensor device (101), and wherein the second set of sensing data (20) comprising biometric sound data acquired at the second sensor device (102).

36. A method according to claim 34, wherein the at least one sensor device (100) includes the first sonic sensor (301) and the second sonic sensor (302).

37. A method according to any of claims 21 to 36, wherein filtering the first set of sensing data to remove data associated with non-biometric sounds comprises applying an artificial intelligence model.

38. A method according to claim 37, wherein the artificial intelligence model comprises at least one of: a statistical model, a machine learning model, a deep learning model, and / or a convolution neural network.

39. A method according to claim 37 or 38, wherein the artificial intelligence model has been trained using data sets comprising each phase of a four-phase migrating motor complex(MMC) cycle.

40. A system (1) according to any one of claims 1 to 20 including a computer readable medium comprising instructions which, when executed by the processor (800), cause the processor (800) to perform the method of any of claims 21 to 39.

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